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Non-equidistant integration for gMAM #30

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oameye opened this issue Mar 21, 2024 · 0 comments
Open

Non-equidistant integration for gMAM #30

oameye opened this issue Mar 21, 2024 · 0 comments
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help wanted Extra attention is needed performance Improving performance of existing functions

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@oameye
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oameye commented Mar 21, 2024

The current bottleneck in gMAM is the interpolation step which has to be doen every optimization step. This also makes it that any other solver than gradient descent and LBGFS is not usable in the current implementation with Optim.jl. The reason why we have to interpolate is to make the path equidistant to allow for easy integration needed for the action. Is this the only reason? In case so we could opt for non-equidistant integration to compute the action.

@reykboerner reykboerner added performance Improving performance of existing functions help wanted Extra attention is needed labels Mar 21, 2024
@oameye oameye added this to the Release version 1.0 milestone Mar 27, 2024
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Labels
help wanted Extra attention is needed performance Improving performance of existing functions
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